10 citations · 19 across the 15 of their papers we have counts for
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Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties
Yassir Fathullah, Guoxuan Xia, Mark Gales
Efficiently and reliably estimating uncertainty is an important objective in deep learning. It is especially pertinent to autoregressive sequence tasks, where training and inferenc…
Who Needs Decoders? Efficient Estimation of Sequence-level Attributes
Yassir Fathullah, Puria Radmard, Adian Liusie +1
State-of-the-art sequence-to-sequence models often require autoregressive decoding, which can be highly expensive. However, for some downstream tasks such as out-of-distribution (O…
Self-Distribution Distillation: Efficient Uncertainty Estimation
Yassir Fathullah, Mark J. F. Gales
Deep learning is increasingly being applied in safety-critical domains. For these scenarios it is important to know the level of uncertainty in a model's prediction to ensure appro…